Senior Enterprise Account Executive

DoorDash, Observe.AI, and AWS partner to scale customer-centric AI across 19,000 agents. Jul 14, 2026, 04:51 ET Nearly 100% automated quality coverage enables real-time insight, behavioral analysis, and faster action to improve customer experience REDWOOD CITY, Calif., July 14, 2026 /PRNewswire/ - Observe.AI today shared the impact of its collaboration with DoorDash and Amazon Web Services (AWS), which has transformed DoorDash's customer support operations through nearly 100% automated interaction evaluations across 19,000 agents - driving real-time hotspot detection, deeper sentiment visibility, and stronger quality consistency at scale. The collaboration marks a significant milestone in DoorDash's broader AI strategy - positioning customer experience at the forefront of responsible AI adoption and operational innovation. Moving From Checkbox QA to Customer Insight As DoorDash expanded globally, traditional manual QA processes - based on limited sampling and binary scoring - could no longer keep pace. The company sought a more scalable, diagnostic approach that would move beyond compliance and uncover the true behavioral drivers behind customer pain points. Through a partnership with Observe.AI, powered in part by AWS transcription and AI model infrastructure, DoorDash built a conversational intelligence platform capable of evaluating nearly 100% of customer interactions automatically. "AI is incredibly important to DoorDash, especially in customer experience," said Xenia Strunnikova, Head of Customer Experience, Fraud, Trust & Safety S&O at DoorDash. "We didn't want automation for its own sake. We wanted to better understand what drives customer sentiment, move beyond binary scoring, and put the customer at the center of our decisions. This partnership enabled us to do that at scale." Automation allowed DoorDash to shift human quality teams away from manual scoring and toward higher-value analysis - identifying subjective issues, understanding behavioral drivers, and ensuring customer safety and fairness. From Days to Near Real-Time Hotspot Detection Observe.AI's conversational intelligence signals, including sentiment, comprehension metrics, and behavioral indicators, enable DoorDash to infer satisfaction even when customers do not explicitly provide feedback. These signals have significantly accelerated issue detection. Emerging product friction points, such as DashPass concerns or new feature launches, that previously took days or weeks to uncover can now be surfaced in near real time. "Listening to customers at scale is hard," said Joaquin Dufeu, Director of Strategy & Operations for Customer Experience & Integrity (CXI) with DoorDash. "With nearly 100% coverage, we can proactively identify hotspots we might never have seen before. What used to take days now happens almost immediately. That changes how we operate - and how quickly we can improve the experience." This shift supports DoorDash's long-term ambition to move toward real-time operational response, enabling faster product iteration and more proactive customer care. Strengthening Responsible AI Adoption The initiative also reinforces DoorDash's commitment to responsible AI implementation. Rather than replacing human judgment, automation augments teams with objective signals and comprehensive visibility - creating more consistent coaching, clearer partner alignment, and stronger accountability across BPO relationships. A Platform Built Through Iterative Partnership The companies describe the effort as co-creation - building and refining signals together in iterative cycles to ensure the platform reflects DoorDash's operational realities and customer priorities. "This was never about deploying a tool," said Deepak Kumar, Observe.AI Chief Customer Officer (CCO). "It was about building a platform alongside DoorDash that enables automation, diagnostic insight, and real-time intelligence at enterprise scale. Together with AWS, we're helping power a customer-first AI transformation." Investing in the Customer Experience At its core, the initiative is focused on one outcome: doing better for customers. With full interaction coverage, richer behavioral analysis, and faster insight turnaround, DoorDash can better understand its customers, keep them safe, and drive meaningful operational change - advancing its broader AI roadmap while maintaining trust and empathy at the center of the experience. The companies will continue to iterate on signals, expand real-time capabilities, and deepen their collaboration as part of DoorDash's ongoing AI investment strategy. About Observe.AI Observe.AI is the leading contact center intelligence platform trusted by global enterprises to transform customer engagement. Using advanced AI and real-time conversation intelligence, Observe.AI helps organizations improve customer satisfaction, enhance agent performance, and achieve operational excellence across mission-critical contact center operations. About DoorDash DoorDash is a leading global platform for local commerce, connecting consumers with restaurants, grocery stores, convenience stores, and retailers. Founded in 2013, DoorDash helps local businesses grow and enables fast, reliable delivery across markets worldwide. SOURCE Observe.AI

CMP Research recognizes the future of Agent Assist - and it's agentic. Observe.AI Companion Agent recognized as a Pioneer in the latest CMP Prism for Real-Time Agent Assist Customer service is changing. As AI Agents increasingly automate routine customer interactions, the conversations that reach human agents are becoming more complex, emotional, and business-critical. Today's frontline teams aren't looking for another knowledge base or script - they need an intelligent partner that can understand context, guide decisions, and take action alongside them. That's exactly why Observe.AI, Inc is excited that Observe.AI has been recognized as a Pioneer in the latest CMP Prism for Real-Time Agent Assist and Copilot. The independent analyst evaluation recognizes providers that are advancing the next generation of agent assistance based on analyst research, customer feedback, and market perception. The market is moving beyond traditional agent assist. According to CMP Research, real-time agent assistance has become the top technology investment priority for customer contact leaders, with 51% of organizations planning investments over the next two years. As AI handles more routine interactions, live agents are left managing increasingly complex customer issues, making intelligent assistance more important than ever. But CMP also highlights an important shift in the market: the most advanced solutions are moving from guidance to action. Rather than simply surfacing knowledge or recommending responses, next-generation solutions proactively complete work in parallel with the agent - representing a true evolution toward AI-augmented workforces. More than guidance. A true AI companion. Companion Agent is purpose-built for today's AI-powered contact center, where human agents and AI work together throughout every customer interaction. It supports frontline teams across the entire conversation lifecycle: * Before the interaction, Companion Agent prepares agents with customer history, previous conversations, profile information, and intent so they begin every conversation with complete context. * During the interaction, it listens in real time, understands conversation context, surfaces relevant knowledge, prompts compliance actions, identifies behavioral signals, provides coaching, and triggers workflows as the conversation unfolds. * After the interaction, it automatically generates editable summaries, captures key details, updates business systems, classifies dispositions, and recommends coaching opportunities to improve future performance. Rather than acting as another window agents must monitor, Companion Agent becomes an active participant that helps reduce effort, improve consistency, and accelerate resolution. Built for the next era of customer experience. Legacy agent assist solutions were designed to provide static guidance. Companion Agent was designed for an agentic future. Built on agentic AI, business users can configure and continuously improve guidance using natural language instead of complex rules or workflows. That means organizations can deploy faster, adapt more quickly, and continuously optimize how AI supports their frontline teams as customer needs evolve. The direction of the industry reinforces this approach. CMP identifies emerging capabilities like real-time coaching, proactive actions, sentiment awareness, and autonomous knowledge improvements as defining characteristics of the next generation of agent assist. Recognition that reflects where CX is headed. Being recognized as a Pioneer in the CMP Prism is meaningful because it reflects more than today's capabilities - it recognizes where customer experience technology is headed. As organizations deploy AI Agents to automate customer interactions, the role of human agents becomes even more valuable. Success will depend on equipping those agents with intelligent companions that don't just recommend the next step - but help them complete the work. Download the latest CMP Prism for Real-Time Agent Assist to learn more about the trends shaping the future of AI-powered agent assistance and why Observe.AI was recognized as a Pioneer. John McMullan Director of AI Agent Marketing July 2, 2026 No items found.

Move fast without breaking things. Agent Harness provides isolated workspaces & controlled rollouts for rapid development Safely scaling production AI: the power of isolated Workspaces and controlled rollouts. Operating AI agents in an enterprise contact center environment is a high-stakes endeavor. When agents are actively answering calls, following complex policies, authenticating customers, and triggering business workflows, the work doesn't stop after the initial launch. In fact, that's when the real challenge begins. Customer behavior shifts, business policies evolve, and new edge cases emerge daily. To keep up, production agents must adapt quickly. However, modifying a live system can easily disrupt routing accuracy, compliance, containment rates, and the overall customer experience. You can't just edit a live agent and hope for the best. To solve this, Observe.AI built Agent Harness: a structured operating layer designed to manage, test, and release AI agents. Read its first installment of this series here. For teams that need to adapt fast without turning live customer calls into a testing ground, the foundation of this system relies on two critical capabilities: Safe Workspaces and Safe Rollouts. Safe Workspaces: the staging environment for AI Agents. Just like any critical enterprise IT system, you wouldn't push updates to your live IVR routing trees or CRM workflows without rigorous testing and change management. AI agents require that exact same discipline, adapted for conversational logic and business rules. Safe Workspaces provide AI agent builders and operations teams with a completely isolated staging environment to modify an agent without affecting the live production version. Within this workspace, teams can safely experiment with and adjust: * Prompt logic and system instructions * Policy rules and workflow steps * Fallback behavior and escalation criteria * Knowledge base references The "live wire" Reality of agent updates. Agent behavior is highly interconnected. A minor tweak to a prompt can drastically alter how the agent handles customer intent. A simple policy update might change an entire workflow path, while a new fallback rule could dictate when a customer gets prematurely escalated to a live agent. Safe Workspaces allow AI agent builders to view side-by-side comparisons of every change. They can track issues directly within the platform and promote updates through strict, role-based approval workflows - ensuring that every adjustment is reviewed for compliance and accuracy before it ever touches a real customer interaction. Safe Rollouts: incremental deployment and total visibility. Once an update is ready and approved, governance must extend directly into deployment. Treating agent updates as massive, all-or-nothing launches is a recipe for operational risk. Safe Rollouts allow teams to deploy changes incrementally. Through the rollout system, teams can: * Select a specific, approved workspace to release from. * Tag every release with a clear, documented description. * Attach evaluation results to prove operational readiness. * Route the update to a limited percentage of live traffic to test the waters. 1-Click rollbacks and version tracking. If a release does not perform exactly as expected in the real world, your IT and ops teams aren't stuck putting out fires - they can initiate a rollback with a single click. This means agent builders can test a revised authentication step or measure a new routing rule with a small subset of traffic before expanding it across the entire contact center. Crucially, Safe Rollouts enable rigorous version tracking. At an enterprise scale handling millions of interactions, broad averages can easily mask critical problems. If there is a sudden spike in transfers to human agents or a missed compliance disclosure, teams shouldn't be left guessing. Because every interaction is tied to the specific agent version that handled it, your teams can trace anomalies back to the exact release, workspace, and change that caused it. Moving fast without breaking things. Ultimately, AI moves fast, and customer operations must move just as quickly. AI agent builders and operations leaders - those closest to the customer and the business realities - need the autonomy to make improvements when they spot friction or outdated policies. By utilizing Safe Workspaces and Safe Rollouts, teams are no longer slowed down by brittle release processes, nor are they forced to operate outside of IT governance just to get things done. They have a system built for inspection, precise deployment, and instant rollback - giving your enterprise the confidence to constantly improve production AI without ever losing control. Aashraya Sachdeva Director, AI Agents May 28, 2026